Method and device for target tracking

Abstract

The present disclosure provides a method and a device for target tracking. The method includes: obtaining a primary forecasting model and a verification model of a target, the primary forecasting model containing low-level features of the target and the verification model containing high-level features of the target; obtaining a current frame of a video image and determining a tracking region of interest (ROI) and a motion-confining region in the current frame based on a latest status of the target, wherein the tracking ROI moves in accordance to a movement of the target; forecasting a status of the target in the current frame in the tracking ROI based on the primary forecasting model; and determining a target image containing the target based on the status of the target in the current frame. The method further includes extracting high-level features of the target from the target image.

Description

CROSS-REFERENCES TO RELATED APPLICATIONS[0001]This application claims the priority of Chinese Patent Application No. 201610137587.X filed on Mar. 10, 2016, the entire content of which is incorporated herein by reference.FIELD OF THE DISCLOSURE[0002]The present disclosure relates to the field of tracking technologies and, more specially, relates to a method and a device for target tracking.BACKGROUND[0003]Video surveillance is the physical base for real-time monitoring of important places such as enterprises, commercial sites, and parks. The management department can obtain useful data, images and / or audio information from the video surveillance. With the rapid development and popularization of computer applications, the principles of video surveillance have been widely applied to the single-target-gesture tracking systems. A single-target-gesture tracking system can track and recognize a user's target gesture, and implement certain control functions according to the gesture.[0004]Ho...

AI Technical Summary

Benefits of technology

The patent describes a method for improving the efficiency and accuracy of target tracking in a video system. The method uses the characteristics of the target's motion and the previous frames to determine the most likely region where the target will appear in the next frame. This reduces the search area and avoids unnecessary matching at irrelevant positions, resulting in more accurate tracking. The method also helps to prevent tracking drift and errors, and can serve as a reminder to the user not to move their gesture too quickly. Overall, this method improves the performance of target tracking in video systems.

Problems solved by technology

However, during the tracking of a gesture through a conventional single-target-gesture tracking system, tracking loss and / or tracking drift due to the interference by a target similar to a human's hand occur when the hand gesture changes.

Therefore, a conventional single-target-gesture tracking system has low tracking efficiency and poor robustness.

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